一個可理解的圖示，能夠減少司機心理負荷和操作時間於駕駛和圖示識別共用時間。這個研究發展一個診斷工具以查明難以辨認的圖示其原因，以重新設計現有的圖示。先前的研究所示，其實驗選擇了34個難以辨認的圖示，藉由經驗豐富的司機其識別率已經低於 80% (Chi and Dewi, 2014)。由14位經驗豐富的司機參與實驗 (Hsieh, 2014)，每位受測者被要求一個接著一個觀看所有難以辨認的圖示，基於三個階段的圖示可理解性、 易讀性、 識別性和解釋性 (Campbell et al, 2004) 和理解字母數位物件 (Sanders, 1993) 以探討這些圖示的難以辨認其可能的原因。具體問題包括每個圖示是否可見的、熟悉的、有意義的和有吸引力的，以及受測者是否有更好設計的任何建議。所有的答案可以進一步分為更多特定 Yes/No 決策規則，例如，圖示是否大到足以看見，物件是否清晰。決策表用來組織所有的決策規則基於圖示理解和七個類別的圖示設計，並確保這些決策規則的邏輯和互斥的三個階段 (Chi, Tseng, & Jang, 2012)。所有測試的圖示關聯與決策規則，決策表可以轉化為決策樹圖，以便重新設計這些難以辨認的圖示。決策樹可被驗證是否每個難以辨認的圖示，能夠透過這些決策規則輕鬆地重新設計圖示。本研究將創造重新設計一組新的圖示來替換所有難以辨認的圖示，證明決策樹是一個非常有效的診斷工具圖示，用以評估與重新設計。

A comprehensible icon can reduce mental load and operation time for the driver to time share between driving and icon recognition. This study developed a diagnostic tool to identify the causes of poorly recognised icons that could be used for the redesign of existing icons. Thirty-four poorly recognized icons were selected for the current experiment because they had a below 80% recognition rate by experienced drivers in a previous study (Chi and Dewi (2014). Fourteen experienced drivers participated in the experiment conducted by (Hsieh, 2014), where each participant was asked to review all poorly recognized icons one by one based on three stages of icon comprehension, legibility, recognition and interpretation (Campbell et al, 2004) and the three aspects of understanding alphanumerical objects (Sanders, 1993) to explore possible causes for poor recognition of these icons. Specific questions include whether each icon is visible, familiar, meaningful, and attractive, and if the participants have any suggestion for a better alternative design. All the answers can be further divided into more specific Yes/No decision rules, e.g., whether the icon is big enough to be visible, whether the object is legible. A decision table is used to organize all the decision rules based on three stages of icon comprehension and seven categories of icon design, and to ensure these decision rules are logical and mutually exclusive (Chi, Tseng, & Jang, 2012). By associating all the tested icons with the decision rules, the decision table can be transformed into a decision tree illustration to facilitate the redesign of these poorly recognized icons. The decision tree can be validated by whether each poorly recognized icon can be redesigned easily based on these decision rules. A new set of redesigned icons would be created to replace all the poorly recognized icons to prove that the decision tree is a very effective diagnostic tool for icon evaluation and redesign.

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